The present invention pertains to the art of analyzing hypothetical scenarios that can be described by narrative text and, more particularly, to analyzing a hypothetical scenario based on a knowledge base of narrative text containing information describing evidence for various events that may be part of a hypothetical scenario and organizing the events and information in a format that may be statistically analyzed using mathematical tools. The mathematical tools include representing both the information contained in the knowledge base and the hypothetical scenarios in a tensor format allowing associating a bounded positive number, the score, to hypothetical scenarios given the evidence contained in the knowledge base.
Currently, several nations are facing threats from violent actions taken against them from foreign countries, international terrorists and/or internal organizations that resort to violent actions. In order to counteract or prevent these violent acts, organizations, such as government agencies and in some cases corporations, employ analysts to try to predict when such violent actions may occur.
Generally, the organizations start by collecting information about suspected groups. Such information may be gathered from several sources. For example, computer based communications, such as E-mails, may be intercepted and the contents or a summaries of the E-mails stored. Telephone intercepts may be translated and also stored, usually as narrative text. Other information may come from police reports describing the results of searches or people that have been arrested. In some cases, reports may come from military units that capture people or computers having information of interest. In each case, threat analysts usually express scenarios as narrative text using written language. Each entry will generally describe basic information about an event. Specifically, the entry often will include an entity who committed certain acts, what they did, when they did it, where the acts took place, etc. However, the entries and other evidence are often fragmentary and not organized in a meaningful way.
While such information may be useful directly and each narrative report may provide valuable information, often truly useful information needed to predict a violent action may only become apparent when information from various different sources is cross-referenced and analyzed together. Even then the task of figuring out if the information is directed to one or more distinct events is particularly difficult. Collecting and organizing information from a large number of sources and converting the information into a format that can be easily analyzed has proven to be a difficult task of interest in developing tools that predict the likelihood a certain event will or has occurred.
U.S. Pat. No. 7,225,122 proposes a method for analyzing computer communications to produce indications and warnings of dangerous behavior. The method includes collecting a computer-generated communication, such as an E-mail, and parsing the collected communication to identify categories of information that may be indicative of the author's state of mind. When the system identifies an author who represents a threat, then appropriate action may be taken. However, the method only focuses on electronic communications and determining the state of mind of an author. The method does not address any other predictors of when and where a violent event may occur. Also, the method does not organize the information in a format that may be statistically analyzed by mathematical tools. Instead, the method focuses on using Weintraub algorithms to profile psychological states of an author.
U.S. Patent Application Publication No. 2007/0061758 discloses a method for processing natural language so that text communications may be displayed as diagrammatic representations. This patent document does not address pulling information from different sources and organizing the information.
As can be seen from the above discussion, there exists a need in the art for a method providing a structural representation of a scenario that takes narrative text from various sources and produces a format that may be statistically analyzed with mathematical tools and more particularly to develop mathematical tools and algorithms that allow analysts to effectively anticipate events given fragmentary evidence stored in a knowledge base represented by a semantic graph and to assign a score or probability to each event to determine a probability of its occurrence.